Normal values for body composition in adults are better represented by continuous reference ranges dependent on age and BMI.

BACKGROUND & AIMS: Reference values for body composition parameters like skeletal muscle mass index (SMI) depend on age and BMI. To ensure reference intervals reflect these changes, they have traditionally been separated into groups of young adults based on sex and BMI. However, this static stratification oversimplifies the dynamic and gradual changes of body composition with increasing age and BMI. The aim was therefore to provide continuous reference ranges for body composition parameters. METHODS: Cross-sectional data of 1958 healthy men and women with an age between 18 and 97 years and a BMI between 17.1 und 45.6 kg/m2 were obtained between 2011 and 2019. Multiple regression analyses stratified by sex with age, age2 and BMI as independent variables were conducted to predict fat mass index (FMI), visceral adipose tissue (VAT), SMI, appendicular lean soft tissue index (ALSTI) and the ratio between extracellular to total body water (ECW/TBW). RESULTS: The regression models explained between 61 (VAT in women and ALSTI in men) and 93% of the variance in the respective body composition parameters (FMI in women). Age had only a minor impact (2-16%) whereas BMI substantially increased the explained variance of reference models for FMI, VAT and ALSTI (total explained variance 61-93%). In SMI, age is a major determinant of the explained variance (36% in men and 38% in women) with BMI equally contributing to the explained variance (total explained variance 72% in men and 75% in women). For ECW/TBW-ratio, age nearly completely explained the variance (79% in men and 74% in women) whereas BMI added only 2-3% to the explained variance. CONCLUSIONS: In conclusion, the derived continuous reference ranges are expected to improve body composition evaluation especially in very overweight and very old persons. Future studies applying these reference equations need to validate these assumptions. STUDY REGISTRATION, CLINICALTRIALS.GOV: NCT01368640, NCT01481285, NCT03779932, NCT04028648.

Determinants of bone mass in older adults with normal- and overweight derived from the crosstalk with muscle and adipose tissue.

Lower bone mass in older adults may be mediated by the endocrine crosstalk between muscle, adipose tissue and bone. In 150 community-dwelling adults (59-86 years, BMI 17-37 kg/m2; 58.7% female), skeletal muscle mass index, adipose tissue and fat mass index (FMI) were determined. Levels of myokines, adipokines, osteokines, inflammation markers and insulin were measured as potential determinants of bone mineral content (BMC) and density (BMD). FMI was negatively associated with BMC and BMD after adjustment for mechanical loading effects of body weight (r-values between -0.37 and -0.71, all p < 0.05). Higher FMI was associated with higher leptin levels in both sexes, with higher hsCRP in women and with lower adiponectin levels in men. In addition to weight and FMI, sclerostin, osteocalcin, leptin × sex and adiponectin were independent predictors of BMC in a stepwise multiple regression analysis. Muscle mass, but not myokines, showed positive correlations with bone parameters that were weakened after adjusting for body weight (r-values between 0.27 and 0.58, all p < 0.01). Whereas the anabolic effect of muscle mass on bone in older adults may be partly explained by mechanical loading, the adverse effect of obesity on bone is possibly mediated by low-grade inflammation, higher leptin and lower adiponectin levels.

Network-based quantitative trait linkage analysis of microbiome composition in inflammatory bowel disease families.

Introduction: Inflammatory bowel disease (IBD) is characterized by a dysbiosis of the gut microbiome that results from the interaction of the constituting taxa with one another, and with the host. At the same time, host genetic variation is associated with both IBD risk and microbiome composition. Methods: In the present study, we defined quantitative traits (QTs) from modules identified in microbial co-occurrence networks to measure the inter-individual consistency of microbial abundance and subjected these QTs to a genome-wide quantitative trait locus (QTL) linkage analysis. Results: Four microbial network modules were consistently identified in two cohorts of healthy individuals, but three of the corresponding QTs differed significantly between IBD patients and unaffected individuals. The QTL linkage analysis was performed in a sub-sample of the Kiel IBD family cohort (IBD-KC), an ongoing study of 256 German families comprising 455 IBD patients and 575 first- and second-degree, non-affected relatives. The analysis revealed five chromosomal regions linked to one of three microbial module QTs, namely on chromosomes 3 (spanning 10.79 cM) and 11 (6.69 cM) for the first module, chr9 (0.13 cM) and chr16 (1.20 cM) for the second module, and chr13 (19.98 cM) for the third module. None of these loci have been implicated in a microbial phenotype before. Discussion: Our study illustrates the benefit of combining network and family-based linkage analysis to identify novel genetic drivers of microbiome composition in a specific disease context.

Analysis of the adiponectin paradox in healthy older people.

BACKGROUND: It remains unknown why adiponectin levels are associated with poor physical functioning, skeletal muscle mass and increased mortality in older populations. METHODS: In 190 healthy adults (59-86 years, BMI 17-37 kg/m2 , 56.8% female), whole body skeletal muscle mass (normalized by height, SMI, kg/m2 ), muscle and liver fat were determined by magnetic resonance imaging. Bone mineral content (BMC) and density (BMD) were assessed by dual X-ray absorptiometry (n = 135). Levels of insulin-like growth factor 1 (IGF-1), insulin, inflammation markers, leptin and fibroblast growth factor 21 were measured as potential determinants of the relationship between adiponectin and body composition. RESULTS: Higher adiponectin levels were associated with a lower SMI (r = -0.23, P < 0.01), BMC (r = -0.17, P < 0.05) and liver fat (r = -0.20, P < 0.05) in the total population and with higher muscle fat in women (r = 0.27, P < 0.01). By contrast, IGF-1 showed positive correlations with SMI (r = 0.33), BMD (r = 0.37) and BMC (r = 0.33) (all P < 0.01) and a negative correlation with muscle fat (r = -0.17, P < 0.05). IGF-1 was negatively associated with age (r = -0.21, P < 0.01) and with adiponectin (r = -0.15, P < 0.05). Stepwise regression analyses revealed that IGF-1, insulin and leptin explained 18% of the variance in SMI, and IGF-1, leptin and age explained 16% of the variance in BMC, whereas adiponectin did not contribute to these models. CONCLUSIONS: Associations between higher adiponectin levels and lower muscle or bone mass in healthy older adults may be explained by a decrease in IGF-1 with increasing adiponectin levels.

Issues related to the assessment of energy balance during short-term over-, under- and refeeding in normal weight men.

BACKGROUND: In humans, it is unclear how different estimates of energy balance (EB) compare with each other and whether the resulting changes in body weight (bw) and body composition (BC) are predictable and reproducible. METHODS: This is a secondary data analysis of effects of sequential 7d over- (OF), 21d under- (UF) and 14d refeeding (RF) on EB. Energy intake (EI) was controlled at +/- 50% of energy needs in a 32 normal weight men (see Am J Clin Nutr. 2015; 102:807-819). EB was calculated (i) directly from the difference between EI and energy expenditure (EE) and (ii) indirectly from changes in BC. Changes in fat mass (FM) were compared with predicted changes according to Hall et al. (Lancet 2011; 378:826-37). Finally, within-subject reproducibility of changes in bw and BC was tested in a subgroup. RESULTS: There were interindividual and day-by-day variabilities in changes in bw and BC. During OF and RF, the two estimates of EB were similar while with UF the indirect approach underestimated the direct estimate by 10593 ± 7506 kcal/21d (p < 0.001). Considerable differences became evident between measured and predicted changes in FM. Adjusting measured for predicted values did not reduce their interindividual variance. During UF, changes in bw and BC were reproducible, while corresponding changes during OF were not. CONCLUSION: During hypercaloric nutrition the direct estimate of EB corresponded to the indirect estimate whereas this was not true during UF. Changes in bw and BC in response to OF were not reproducible while they were during UF.

Linkage analysis identifies novel genetic modifiers of microbiome traits in families with inflammatory bowel disease.

Dysbiosis of the gut microbiome is a hallmark of inflammatory bowel disease (IBD) and both, IBD risk and microbiome composition, have been found to be associated with genetic variation. Using data from families of IBD patients, we examined the association between genetic and microbiome similarity in a specific IBD context, followed by a genome-wide quantitative trait locus (QTL) linkage analysis of various microbiome traits using the same data. SNP genotypes as well as gut microbiome and phenotype data were obtained from the Kiel IBD family cohort (IBD-KC). The IBD-KC is an ongoing prospective study in Germany currently comprising 256 families with 455 IBD patients and 575 first- and second-degree relatives. Initially focusing upon known IBD risk loci, we noted a statistically significant (FDR<0.05) association between genetic similarity at SNP rs11741861 and overall microbiome dissimilarity among pairs of relatives discordant for IBD. In a genome-wide QTL analysis, 12 chromosomal regions were found to be linked to the abundance of one of seven microbial genera, namely Barnesiella (chromosome 4, region spanning 10.34 cM), Clostridium_XIVa (chr4, 3.86 cM; chr14, two regions spanning 7.05 and 13.02 cM respectively), Pseudoflavonifractor (chr7, 12.80 cM) Parasutterella (chr14, 8.26 cM), Ruminococcus (chr16, two overlapping regions spanning 8.01 and 16.87 cM, respectively), Roseburia (chr19, 7.99 cM), and Odoribacter (chr22, three regions spanning 0.89, 5.57 and 1.71 cM, respectively), as well as the Shannon index of α diversity (chr3, 1.47 cM). Our study thus shows that, in families of IBD patients, pairwise genetic similarity for at least one IBD risk locus is associated with overall microbiome dissimilarity among discordant pairs of relatives, and that hitherto unknown genetic modifiers of microbiome traits are located in at least 12 human genomic regions.

Plasma boron concentrations in the general population: a cross-sectional analysis of cardio-metabolic and dietary correlates.

PURPOSE: Experimental evidence suggests positive effects of boron on health and metabolism, but human data are still scarce. We aimed to identify dietary and cardio-metabolic correlates of plasma boron concentrations in the general population. METHODS: In a community-based sample (n = 899, 57% men, mean age 61 years), plasma boron (median [IQR]: 33.80 µg/L [25.61; 44.65]) concentrations were measured by inductively coupled plasma-mass spectrometry. Overall (PDI), healthy (hPDI), and unhealthy (uPDI) plant-based diet indices were derived from a validated food frequency questionnaire. Reduced rank regression (RRR) yielded a dietary pattern explaining 30% of the variation of circulating boron. Cross-sectional associations of dietary indices and cardio-metabolic traits with plasma boron concentrations were assessed using multivariable-adjusted linear regression analysis. RESULTS: The RRR pattern was characterized by high intake of fruits, nuts/seeds, tea, wine and low intake of e.g. bread, poultry, processed meat, chocolate/sweets, and soft drinks. 10-point increments in PDI, hPDI, and uPDI were associated with 8.7% (95% CI: 4.2; 13.4), 10.4% (95% CI: 6.6; 14.3), and -8.8% (95% CI: -12.1; -5.4) change in plasma boron concentrations, respectively. Age and phosphate were directly, while BMI, plasma lipid concentrations, and CRP were inversely associated with circulating boron. Plasma boron concentrations were higher in summer vs. winter, in individuals taking vs. not taking antihypertensive medication, and in individuals with high or medium vs. low education level. CONCLUSION: Higher plasma boron concentrations appeared to associate with a healthier diet, were related to lower BMI and a more favorable cardio-metabolic risk profile, and showed seasonal variations.

Post-diagnostic reliance on plant-compared with animal-based foods and all-cause mortality in omnivorous long-term colorectal cancer survivors.

BACKGROUND: Plant-rich diets are associated with lower cardiometabolic risks and longer survival in the general population, but their association with mortality in cancer survivors is still unclear. OBJECTIVES: We aimed to examine the associations of 3 postdiagnostic plant-based diet indices with all-cause mortality in omnivorous long-term colorectal cancer (CRC) survivors. METHODS: Diet was assessed with FFQs at a median of 6 years after diagnosis in 1404 CRC survivors (56% male; median age, 69 years) in a Northern German prospective cohort study. An overall, a healthful plant-based, and an unhealthful plant-based diet index were derived by scoring intakes of animal foods reversely and intakes of healthy (whole grains, vegetables, fruits, legumes, nuts, oils, tea/coffee) and less healthy plant foods (refined grains, fruit juices, sugar-sweetened beverages, potatoes, sweets/desserts) positively or reversely, depending on the index. Vital status follow-up was conducted via population registries. Cox proportional hazards regression was applied to estimate HRs for all-cause mortality according to plant-based diet adherence. RESULTS: Within 7 years (median) after diet assessment, 204 deaths occurred. The overall plant-based diet index displayed a significant, inverse association with all-cause mortality (HR per 10-point increase in diet index, 0.72; 95% CI, 0.57-0.91). Although not statistically significant, higher healthful plant-based diet scores showed a strong tendency towards lower mortality (HR, 0.82; 95% CI, 0.67-1.01). The unhealthful plant-based diet index was associated with higher mortality, but lost statistical significance after multivariable adjustment (HR, 1.19; 95% CI, 0.96-1.48). A subgroup analysis revealed that the tendency towards a positive association of the unhealthful plant-based diet with mortality was restricted to less physically active individuals (<95 metabolic equivalent of task hours/week). CONCLUSIONS: An overall plant-based diet was inversely associated with all-cause mortality in long-term CRC survivors. However, more research is needed to further disentangle the impacts of different qualities of plant-based diets on cancer survivors' health.

Plasma Lithium Levels in a General Population: A Cross-Sectional Analysis of Metabolic and Dietary Correlates.

Initial evidence suggests that lithium might affect life expectancy and the risk for different disease conditions, but most studies were conducted in patients on lithium medication. Little is known about the association of blood lithium levels within the physiological range with cardiometabolic risk factors and diet. We measured plasma lithium in a community-based sample from Northern Germany (samples taken between 2010 and 2012). All participants (aged 25-82 years) underwent standardized examinations and completed a semi-quantitative food frequency questionnaire. Of several variables tested, the estimated glomerular filtration rate (eGFR) was statistically significantly (inversely) associated with lithium levels, mainly in individuals with slightly impaired renal function (eGFR < 75 mL/min/1.73 m2). Besides, lithium levels were positively associated with age and alcohol intake. Using reduced rank regression, we identified a dietary pattern explaining 8.63% variation in plasma lithium levels. Higher lithium levels were associated with higher intakes of potatoes, leafy vegetables, root vegetables, fruits, tea, beer, wine and dietetic products and lower intakes of pasta, rice, pork, chocolate, sweets, soft drinks, other alcoholic beverages, sauces and snacks. Our observations suggest that plasma lithium levels are associated inversely with kidney function, particularly in individuals with slightly impaired renal function, and positively with age and alcohol intake. Lithium at physiological levels was moderately related to an exploratory dietary pattern.

Adherence to a plant-based diet in relation to adipose tissue volumes and liver fat content.

BACKGROUND: Better adherence to plant-based diets has been linked to lower risk of metabolic diseases but the effect on abdominal fat distribution and liver fat content is unclear. OBJECTIVES: We aimed to examine the association between different plant-based diet indices and measures of abdominal fat distribution and liver fat content. METHODS: In a population-based sample of 578 individuals from Northern Germany (57% male, median age 62 y), diet was assessed with a validated FFQ and an overall, a healthy, and an unhealthy plant-based diet index were derived. Participants underwent MRI to assess volumes of visceral and subcutaneous abdominal adipose tissue and liver signal intensity (LSI), a measure of liver fat content. Fatty liver disease (FLD) was defined as log LSI ≥3.0. Cross-sectional associations of the plant-based diet indices with visceral and subcutaneous abdominal fat volumes, LSI, and FLD were assessed in linear and logistic regression analyses. The most comprehensive model adjusted for age, sex, education, smoking, alcohol, physical activity, energy intake, diabetes, hyperlipidemia, and BMI. RESULTS: Higher overall and healthy plant-based diet indices both revealed statistically significant associations with lower visceral and subcutaneous abdominal adipose tissue volumes and with lower odds of FLD in multivariable-adjusted models without BMI. Upon additional adjustment for BMI, only the association of the healthy plant-based diet with visceral adipose tissue remained statistically significant (per 10-point higher healthy plant-based diet index, percentage change in visceral adipose tissue: -4.9%, 95% CI: -8.6%, -2.0%). None of the plant-based diet indices was associated with LSI. The unhealthy plant-based diet index was unrelated to any of the abdominal or liver fat parameters. CONCLUSIONS: Adherence to healthy plant-based diets was associated with lower visceral adipose tissue. None of the other examined associations remained statistically significant after adjustment for BMI.

Health-related quality of life in long-term survivors of colorectal cancer and its association with all-cause mortality: a German cohort study.

BACKGROUND: The group of colorectal cancer (CRC) survivors continues to grow worldwide. Understanding health-related quality of life (HRQOL) determinants and consequences of HRQOL impairments in long-term CRC survivors may help to individualize survivorship care plans. We aimed to i) examine the HRQOL status of CRC long-term survivors, ii) identify cross-sectional sociodemographic and clinical correlates of HRQOL, and iii) investigate the prospective association of HRQOL after CRC diagnosis with all-cause mortality. METHODS: We assessed HRQOL within a Northern German cohort of 1294 CRC survivors at a median of 6 years after CRC diagnosis using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). Cross-sectional correlates of different HRQOL dimensions were analyzed using multivariable-adjusted logistic regression models with HRQOL as a binary variable. With multivariable-adjusted Cox proportional hazards regression models, hazard ratios (HR) of all-cause mortality were estimated per 10-point-increments of an HRQOL summary score, a global quality of life scale, and HRQOL functioning and symptom domains. RESULTS: The median HRQOL summary score was 87 (interquartile range: 75-94). Sex, age, education, tumor location, metastases, other cancers, type of therapy, and current stoma were identified as correlates of different HRQOL scales. After a median follow-up time of 7 years after HRQOL assessment, 175 participants had died. Nearly all HRQOL domains, except for cognitive functioning and diarrhea, were significantly associated with all-cause mortality. A 10-point-increment in the summary score decreased the risk of death by 24% (HR: 0.76; 95% CI: 0.70-0.82). CONCLUSIONS: HRQOL in CRC survivors appeared to be relatively high in the long term. Various clinical and sociodemographic factors were cross-sectionally associated with HRQOL in long-term CRC survivors. Lower HRQOL was associated with increased all-cause mortality. Individualized healthcare programs for CRC survivors (including psychosocial screening and interventions) are needed to detect decreased HRQOL and to further improve long-term HRQOL and survival.

The case of GWAS of obesity: does body weight control play by the rules?

As yet, genome-wide association studies (GWAS) have not added much to our understanding of the mechanisms of body weight control and of the etiology of obesity. This shortcoming is widely attributed to the complexity of the issues. The appeal of this explanation notwithstanding, we surmise that (i) an oversimplification of the phenotype (namely by the use of crude anthropometric traits) and (ii) a lack of sound concepts of body weight control and, thus, a lack of a clear research focus have impeded better insights most. The idea of searching for polygenetic mechanisms underlying common forms of obesity was born out of the impressive findings made for monogenetic forms of extreme obesity. In the case of common obesity, however, observational studies on normal weight and overweight subjects never provided any strong evidence for a tight internal control of body weight. In addition, empirical studies of weight changes in normal weight and overweight subjects revealed an intra-individual variance that was similar to inter-individual variance suggesting the absence of tight control of body weight. Not least, this lack of coerciveness is reflected by the present obesity epidemic. Finally, data on detailed body composition highlight that body weight is too heterogeneous a phenotype to be controlled as a single entity. In summary GWAS of obesity using crude anthropometric traits have likely been misled by popular heritability estimates that may have been inflated in the first place. To facilitate more robust and useful insights into the mechanisms of internal control of human body weight and, consequently, the genetic basis of obesity, we argue in favor of a broad discussion between scientists from the areas of integrative physiologic and of genomics. This discussion should aim at better conceived studies employing biologically more meaningful phenotypes based on in depth body composition analysis. To advance the scientific community-including the editors of our top journals-needs a re-launch of future GWAS of obesity.

Association of Circulating Vitamin E (α- and γ-Tocopherol) Levels with Gallstone Disease.

In addition to well-established risk factors like older age, female gender, and adiposity, oxidative stress may play a role in the pathophysiology of gallstone disease. Since vitamin E exerts important anti-oxidative functions, we hypothesized that circulating vitamin E levels might be inversely associated with prevalence of gallstone disease. In a cross-sectional study, we measured plasma levels of α- and γ-tocopherol using high performance liquid chromatography in a community-based sample (582 individuals; median age 62 years; 38.5% women). Gallstone disease status was assessed by ultrasound. Multivariable-adjusted logistic regression models were used to estimate the association of circulating α- and γ-tocopherol/cholesterol ratio levels with prevalent gallstone disease. Lower probabilities of having gallstone disease were observed in the top (compared to the bottom) tertile of the plasma α-tocopherol/cholesterol ratio in multivariable-adjusted models (OR (Odds Ratio): 0.31; 95% CI (Confidence Interval): 0.13-0.76). A lower probability of having gallstone disease was also observed for the γ-tocopherol/cholesterol ratio, though the association did not reach statistical significance (OR: 0.77; 95% CI: 0.35-1.69 for 3rd vs 1st tertile). In conclusion, our observations are consistent with the concept that higher vitamin E levels might protect from gallstone disease, a premise that needs to be further addressed in longitudinal studies.

Changes in Energy Expenditure with Weight Gain and Weight Loss in Humans.

Metabolic adaptation to weight changes relates to body weight control, obesity and malnutrition. Adaptive thermogenesis (AT) refers to changes in resting and non-resting energy expenditure (REE and nREE) which are independent from changes in fat-free mass (FFM) and FFM composition. AT differs in response to changes in energy balance. With negative energy balance, AT is directed towards energy sparing. It relates to a reset of biological defence of body weight and mainly refers to REE. After weight loss, AT of nREE adds to weight maintenance. During overfeeding, energy dissipation is explained by AT of the nREE component only. As to body weight regulation during weight loss, AT relates to two different set points with a settling between them. During early weight loss, the first set is related to depleted glycogen stores associated with the fall in insulin secretion where AT adds to meet brain's energy needs. During maintenance of reduced weight, the second set is related to low leptin levels keeping energy expenditure low to prevent triglyceride stores getting too low which is a risk for some basic biological functions (e.g., reproduction). Innovative topics of AT in humans are on its definition and assessment, its dynamics related to weight loss and its constitutional and neuro-endocrine determinants.

Beyond BMI: Conceptual Issues Related to Overweight and Obese Patients.

BMI is widely used as a measure of weight status and disease risks; it defines overweight and obesity based on statistical criteria. BMI is a score; neither is it biologically sound nor does it reflect a suitable phenotype worthwhile to study. Because of its limited value, BMI cannot provide profound insight into obesity biology and its co-morbidity. Alternative assessments of weight status include detailed phenotyping by body composition analysis (BCA). However, predicting disease risks, fat mass, and fat-free mass as assessed by validated techniques (i.e., densitometry, dual energy X ray absorptiometry, and bioelectrical impedance analysis) does not exceed the value of BMI. Going beyond BMI and descriptive BCA, the concept of functional body composition (FBC) integrates body components into regulatory systems. FBC refers to the masses of body components, organs, and tissues as well as to their inter-relationships within the context of endocrine, metabolic and immune functions. FBC can be used to define specific phenotypes of obesity, e.g. the sarcopenic-obese patient. Well-characterized obesity phenotypes are a precondition for targeted research (e.g., on the genomics of obesity) and patient-centered care (e.g., adequate treatment of individual obese phenotypes such as the sarcopenic-obese patient). FBC contributes to a future definition of overweight and obesity based on physiological criteria rather than on body weight alone.

Metabolic adaptation to caloric restriction and subsequent refeeding: the Minnesota Starvation Experiment revisited.

BACKGROUND: Adaptive thermogenesis (AT) is the fat-free mass (FFM)-independent reduction of resting energy expenditure (REE) to caloric restriction (CR). AT attenuates weight loss and favors weight regain. Its variance, dynamics, and control remain obscure. OBJECTIVES: Our aims were to address the variance and kinetics of AT, its associations with body composition in the context of endocrine determinants, and its effect on weight regain. DESIGN: Thirty-two nonobese men underwent sequential overfeeding (1 wk at +50% of energy needs), CR (3 wk at -50% of energy needs), and refeeding (2 wk at +50% of energy needs). AT and its determinants were measured together with body composition as assessed with the use of quantitative magnetic resonance, whole-body MRI, isotope dilution, and nitrogen and fluid balances. RESULTS: Changes in body weight were +1.8 kg (overfeeding), -6.0 kg (CR), and +3.5 kg (refeeding). CR reduced fat mass and FFM by 114 and 159 g/d, respectively. Within FFM, skeletal muscle (-5%), liver (-13%), and kidneys (-8%) decreased. CR also led to reductions in REE (-266 kcal/d), respiratory quotient (-15%), heart rate (-14%), blood pressure (-7%), creatinine clearance (-12%), energy cost of walking (-22%), activity of the sympathetic nervous system (SNS) (-38%), and plasma leptin (-44%), insulin (-54%), adiponectin (-49%), 3,5,3'-tri-iodo-thyronine (T3) (-39%), and testosterone (-11%). AT was 108 kcal/d or 48% of the decrease in REE. Changes in FFM composition explained 36 kcal, which left 72 kcal/d for true AT. The decrease in AT became significant at ≤3 d of CR and was related to decreases in insulin secretion (r = 0.92, P < 0.001), heart rate (r = 0.60, P < 0.05), creatinine clearance (r = 0.79, P < 0.05), negative fluid balance (r = 0.51, P < 0.01), and the free water clearance rate (r = -0.90, P < 0.002). SNS activity and plasma leptin, ghrelin, and T3 and their changes with CR were not related to AT. CONCLUSION: During early weight loss, AT is associated with a fall in insulin secretion and body fluid balance. This trial was registered at clinicaltrials.gov as NCT01737034.

Endocrine determinants of changes in insulin sensitivity and insulin secretion during a weight cycle in healthy men.

OBJECTIVE: Changes in insulin sensitivity (IS) and insulin secretion occur with perturbations in energy balance and glycemic load (GL) of the diet that may precede the development of insulin resistance and hyperinsulinemia. Determinants of changes in IS and insulin secretion with weight cycling in non-obese healthy subjects remain unclear. METHODS: In a 6wk controlled 2-stage randomized dietary intervention 32 healthy men (26±4y, BMI: 24±2kg/m2) followed 1wk of overfeeding (OF), 3wks of caloric restriction (CR) containing either 50% or 65% carbohydrate (CHO) and 2wks of refeeding (RF) with the same amount of CHO but either low or high glycaemic index at ±50% energy requirement. Measures of IS (basal: HOMA-index, postprandial: Matsuda-ISI), insulin secretion (early: Stumvoll-index, total: tAUC-insulin/tAUC-glucose) and potential endocrine determinants (ghrelin, leptin, adiponectin, thyroid hormone levels, 24h-urinary catecholamine excretion) were assessed. RESULTS: IS improved and insulin secretion decreased due to CR and normalized upon RF. Weight loss-induced improvements in basal and postprandial IS were associated with decreases in leptin and increases in ghrelin levels, respectively (r = 0.36 and r = 0.62, p<0.05). Weight regain-induced decrease in postprandial IS correlated with increases in adiponectin, fT3, TSH, GL of the diet and a decrease in ghrelin levels (r-values between -0.40 and 0.83, p<0.05) whereas increases in early and total insulin secretion were associated with a decrease in leptin/adiponectin-ratio (r = -0.52 and r = -0.46, p<0.05) and a decrease in fT4 (r = -0.38, p<0.05 for total insulin secretion only). After controlling for GL associations between RF-induced decrease in postprandial IS and increases in fT3 and TSH levels were no longer significant. CONCLUSION: Weight cycling induced changes in IS and insulin secretion were associated with changes in all measured hormones, except for catecholamine excretion. While leptin, adiponectin and ghrelin seem to be the major endocrine determinants of IS, leptin/adiponectin-ratio and fT4 levels may impact changes in insulin secretion with weight cycling. TRIAL REGISTRATION: ClinicalTrials.gov NCT01737034.

Carbohydrate quality and quantity affect glucose and lipid metabolism during weight regain in healthy men.

In this controlled, parallel-group feeding trial, we examined the impact of carbohydrate (CHO) intake and glycemic index (GI) on glucose and lipid metabolism during refeeding after weight loss. Healthy men (n = 32 total, age: 25.5 ± 3.9 y, BMI: 23.5 ± 2.0 kg/m2) overconsumed diets containing either 50% or 65% CHO for 1 wk (+50% of energy requirements) and then underwent 3 wk of calorie restriction (CR; -50%) followed by 2 wk of overconsuming (refeeding, +50%) the same diet but with either a low or high GI (40 vs.70 during CR, 41 vs.74 during refeeding) so that glycemic load (GL; dietary CHO content x GI) differed between groups during all phases. Glucose profiles were assessed by continuous interstitial glucose monitoring, insulin sensitivity (IS) by fasting blood sampling, oral glucose tolerance test (OGTT) and hyperinsulinemic-euglycemic clamp, and liver fat by MRI. Daytime area under the curve-glucose during refeeding was higher with high compared with low GI (P = 0.01) and 65% compared with 50% CHO intake (P = 0.05) and correlated with dietary GL (r = 0.71; P < 0.001). IS increased with CR and decreased again with refeeding in all groups. The decrease in OGTT-derived IS was greater with high- than with low-GI diets (-41 vs. -15%; P-interaction = 0.01) and correlated with dietary GL during refeeding (r = -0.51; P < 0.01). Serum triglycerides (TGs) and liver fat also improved with CR (-17 ± 38 mg/dL and -1.1 ± 1.3%; P < 0.05 and <0.001) and increased again with refeeding (+48 ± 48 mg/dL and +2.2 ± 1.6%; P < 0.001). After refeeding, serum TGs and liver fat were elevated above baseline values with 65% CHO intake only (+59.9 ± 37.5 mg/dL and +1.1 ± 1.7%, P-interaction <0.001 and <0.05). In conclusion, a diet low in GI and moderate in CHO content (i.e., low GL) may have health benefits by positively affecting daylong glycemia, IS, and liver fat.

Impact of glycaemic index and dietary fibre on insulin sensitivity during the refeeding phase of a weight cycle in young healthy men.

Previous studies suggest that a low-glycaemic index (LGI) diet may improve insulin sensitivity (IS). As IS has been shown to decrease during refeeding, we hypothesised that an LGI- v. high-GI (HGI) diet might have favourable effects during this phase. In a controlled nutritional intervention study, sixteen healthy men (aged 26·8 (SD 4·1) years, BMI 23·0 (SD 1·7) kg/m2) followed 1 week of overfeeding, 3 weeks of energy restriction and of 2 weeks refeeding at ^50% energy requirement (50% carbohydrates, 35% fat and 15% protein). During refeeding, subjects were divided into two matched groups receiving either high-fibre LGI or lower-fibre HGI foods (GI 40 v. 74, fibre intake 65 (SD 6) v. 27 (SD 4) g/d). Body weight was equally regained in both groups with refeeding (mean regain 70·5 (SD 28·0)% of loss). IS was improved by energy restriction and decreased with refeeding. The decreases in IS were greater in the HGI than in the LGIgroup (group £ time interactions for insulin, homeostasis model assessment of insulin resistance (HOMAIR), Matsuda IS index (MatsudaISI);all P,0·05). Mean interstitial glucose profiles during the day were also higher in the HGI group (DAUCHGI-LGI of continuous interstitial glucose monitoring: 6·6 mmol/l per 14 h, P»0·04). At the end of refeeding, parameters of IS did not differ from baseline values in either diet group (adiponectin, insulin, HOMAIR, Matsuda ISI, M-value; all P.0·05). In conclusion, nutritional stress imposed by dietary restriction and refeeding reveals a GI/fibre effect in healthy non-obese subjects. LGI foods rich in fibre may improve glucose metabolism during the vulnerable refeeding phase of a weight cycle.

Anxiety and depression in bariatric surgery patients: a prospective, follow-up study using structured clinical interviews.

BACKGROUND: Candidates for bariatric surgery frequently have co-morbid psychiatric problems. METHODS: This study investigated the course and the prognostic significance of preoperative and postoperative anxiety and depressive disorders in 107 extremely obese bariatric surgery patients in a prospective design with face-to-face interviews (SCID) conducted prior to the surgery and postoperatively after 6-12 months and 24-36 months. RESULTS: The point prevalence of depressive disorders but not of anxiety disorders decreased significantly after surgery. Preoperative depressive disorders predicted depressive disorders 24-36 months but not 6-12 months after surgery, whereas preoperative anxiety significantly predicted postoperative anxiety disorders at both follow-up time points. Preoperative lifetime and current depressive disorders were unrelated to postoperative weight loss whereas preoperative lifetime, but not current anxiety disorders were of negative prognostic value for postoperative weight loss. Patients with both depressive and anxiety disorders at baseline (current and lifetime) lost significantly less weight after surgery. Postoperative anxiety disorder was not associated with the degree of weight loss at any follow-up time-point; however postoperative depressive disorder was negatively associated with weight loss at the 24-36 month follow-up assessment point. LIMITATIONS: Missing data, limited statistical power, self-reported height and weight are the limitations of this study. CONCLUSIONS: As opposed to anxiety disorders, the point prevalence of depressive disorders decreased significantly after bariatric surgery. However, the presence of depressive disorders after bariatric surgery significantly predicted attenuated post-surgical improvements and may signal a need for clinical attention.